Contents

1 Overview

The gDRtestData package is intended to store and generate example data that can be used through the gDR suite.

2 Use Cases

2.1 Synthetic data generation

Since gDR is a computational suite for drug response data from any experiment, a synthetic dataset is also needed for testing and exploration.

The basis of this package are two functions to generate the synthetic sets of cell lines and drugs.

cell_lines <- create_synthetic_cell_lines()
drugs <- create_synthetic_drugs()

These base objects can be extended with additional information.

  1. Replicates
cl_rep <- add_data_replicates(cell_lines)
head(cl_rep)
  1. Concentration
cl_conc <- add_concentration(cell_lines)
head(cl_conc)

Or the user can do both with one function:

df_layout <- prepareData(cell_lines, drugs)
head(df_layout)

Additionally, the user may fill in the full response data with the day 0 part.

df_layout_small <- prepareData(cell_lines[seq_len(2), ], drugs[seq_len(4), ])
df_layout_small$Duration <- 72
df_layout_small$ReadoutValue <- 0
df_layout_small_with_Day0 <- add_day0_data(df_layout_small)
head(df_layout_small_with_Day0)

In a further step, the user may generate a set of synthetic results:

  1. Hill coefficient
hill <- generate_hill_coef(cell_lines, drugs) 
  1. EC50 metric
ec50_met <- generate_ec50(cell_lines, drugs) 
  1. E inf metric
einf_met <- generate_e_inf(cell_lines, drugs)

Or the user can create full response data with one function (for single-agent):

response_data <- prepareMergedData(cell_lines, drugs)
head(response_data)

SUMMARY

Step Function Output (data.table)
0 create_synthetic_cell_lines() synthetic cell lines
0 create_synthetic_drugs() synthetic drugs
1 prepareData() cell lines and drug merged with replicates and concentration
2 prepareMergedData() full response data for single-agent
2 prepareComboMergedData() full response data for combo
2 prepareCodilutionData () full response data for co-dilution

2.2 Synthetic object of gDR data model

The gDR data model is built on the MultiAssayExperiments (MAE) structure. A detailed description of the gDR data model can be found in gDRcore package vignette.

In inst/testdata the user may find a set of qs files that are examples of gDR data model for different data types. In the file synthetic_list.yml one can find a list of these datasets. Currently available are:

#> * combo_2dose_nonoise, 
#> * combo_2dose_nonoise2, 
#> * combo_2dose_nonoise3, 
#> * combo_codilution_small, 
#> * combo_codilution, 
#> * combo_matrix_small, 
#> * combo_matrix, 
#> * combo_triple, 
#> * medium, 
#> * small_no_noise, 
#> * small, 
#> * wLigand .

The script generate_example_data.R which shows how to generate and process above-mentioned datasets is in inst/scripts dir. All key functions can be found in package gDRcore in script generate_wrappers.R.

2.3 Annotation data

In inst/annotation_data the user can find CSV files used in gDRcore for testing annotation functions.

2.4 Other

Other files which were not mentioned above are used for testing gDR suite functionality.

SessionInfo

sessionInfo()
#> R Under development (unstable) (2024-01-16 r85808)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 22.04.3 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.19-bioc/R/lib/libRblas.so 
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: America/New_York
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] gDRtestData_1.1.10 BiocStyle_2.31.0  
#> 
#> loaded via a namespace (and not attached):
#>  [1] backports_1.4.1     digest_0.6.34       R6_2.5.1           
#>  [4] bookdown_0.37       fastmap_1.1.1       xfun_0.42          
#>  [7] cachem_1.0.8        knitr_1.45          htmltools_0.5.7    
#> [10] rmarkdown_2.25      lifecycle_1.0.4     cli_3.6.2          
#> [13] sass_0.4.8          data.table_1.15.0   jquerylib_0.1.4    
#> [16] compiler_4.4.0      tools_4.4.0         checkmate_2.3.1    
#> [19] evaluate_0.23       bslib_0.6.1         yaml_2.3.8         
#> [22] BiocManager_1.30.22 jsonlite_1.8.8      rlang_1.1.3